Professor Aarno Palotie, FIMM, University of Helsinki, Finland, at Genomics to Healthcare EU side event, 13 Sept 2019, THL, Helsinki

1. 1
Aarno Palotie, M.D., Ph.D.

2. 2
10 – 20 years
From Discovery to treatment
and prevention

3. 3
Could
genetics
help?

4. 4

5. Y O U R T E S T B E D F O R N E X T G E N E R A T I O N R E S E A R C H & I N N O V A T I O N
INNOVATIVE STUDY DESIGNS
POPULATION
ISOLATE
HEALTH
REGISTERS
BIOBANKS GENOME DATA
+ ++

6. 6
500 000 individuals
~1O % of the
population
500 000
individuals
Combined
genotype and
register data
National Health
Register data
Association analyses
Axiom GWA array
Imputation
FinnGen

7. 7
National
registers Hospital discharge
Hospital procedure
Outpatient visit
Outpatient procedure
Primary care
Primary care procedure
Cancer register
Cause of death
Drug purchase
Drug reimbursement
Register data
for
administration
Register data
for
administration
Register data
for
administration
151167-123J

8. 8
Nationwide registries
10/08/2020

9. 9
Data from every
healthcare visit over a
lifetime

10. 10
The Finnish Biobank Act is Unique
• Registration of biobanks, wide consent and protection
of participants
• Transfer of existing sample and data collections to
biobanks
• Possibility to recontact
• Possibility to collect samples and data from the health
care
• Collaboration with industry
10 Biobanks

11. 11
EARLY SETTLEMENT
• 2000-10 000 years ago
• South and Coast
LATE SETTLEMENT
• 16th century
• multiple bottle necks
EXPANSION
• 18th century – population 250 000
• Today – population 5.4 million
EARLY
SETTLEMENT
LATE
SETTLEMENT

12. 12
Power of a
Genetic
Isolate
Specific damaging genetic variants become enriched and
easy to discover
Reconstructing genomes of Finns (’imputation’) from
inexpensive genotype data is much more accurate than
in the rest of the world

13. 13
500,000 individuals
10% of the population
Existing sample collections: 215,000
Finns
285,000 new sample donors within 6
years
FinnGen 1: 2017-2020
FinnGen 2: 2020-2023

14. 14
Public - Private
Partnership

15. 15
500 000 individuals
~1O % of the
population
500 000
individuals
Combined
genotype and
register data
National Health
Register data
Association analyses
Axiom GWA array
Imputation
FinnGen

16. 16
FinnGen partners

17. 17
314 000 participants, so far
314 000
participants

18. 18
Available new biobank samples and legacy samples (8/2019)
0 50000 100000 150000 200000 250000 300000 350000
Oct 2017
Nov 2017
Dec 2017
Jan 2018
Feb 2018
Mar 2018
Apr 2018
May 2018
June 2018
July 2018
Aug 2018
Sep 2018
Oct 2018
Nov 2018
Dec 2018
Jan 2019
Feb 2019
Mar 2019
Apr 2019
May 2019
June 2019
July 2019
Aug 2019
New samples Legacy samples
At the end of year 2:
• 138,000 legacy samples
• 176,000 new samples
≈ Total of 314,000
available samples

19. 19
FinnGen disease groups of interest (8/2019)
Neurology
N=3,763
Ophtalmology
N=21,869
Pulmonology
N=14,902
Gastroenterology
N=9,697
Rheumatology
N=9,959
Cardiometabolic
N=51,616
Oncology
N=31,969Hospital biobanks &
Terveystalo Biobank
N=130,671 available samples Dermatology
N=7,105

20. 20
Registry data currently included
Diagnoses
Codes: Kela codes
Procedures
Codes: CPT
Diagnoses
Codes: ICD 8/9/10
HILMO
(In-patient registry – 1969 to 2017)
Topology
Codes: ICD-O-3
KELA
(Drug registry – (1964) 1995 to 2017)
Medications
Codes: ATC codes
Causes of death
(1996 to 2017)
Diagnoses
Codes: ICD 8/9/10
Cancer
(1953 to 2016)
Specialist outpatient clinics
(Out-patient registry – 1998 to 2017)
Procedures
Codes: CPT
Diagnoses
Codes: ICD 9/10
Endpoints
Morphology
Codes: ICD-O-3

21. 21
FinnGen ThermoFisher Axiom custom
array
Covers coding variation down to .01% frequency and offers complete coverage of disease alleles enriched
through the founding bottleneck

22. 22
August 2019 data freeze 181 000
individuals
0
50000
100000
140000
180000
210000
250000
300000
320000
320000
390000
390000
460000
500000
FINNGEN DATA FREEZES
EVERY 6 MONTHS

23. 23
Data release 4 in numbers
• 183,694 samples with genotypes
• 189,328 samples with phenotypes
• 181,821 individuals with genotypes and phenotypes
• 2,443 endpoints (n>100)
• Detailed longitudinal data in the Sandbox, 40 million drug
purchases and ICD codes, 72 million health care events

24. 24
Data freeze 4
• In demo phenotypes:
• 124 genome wide significant loci
• 20 novel
• 16 have has a Finnish enriched lead variant

25. 25
Selected phenotypes

26. 26
Data protection
PARTICIPATION IS VOLUNTARY AND THE
CONSENT CAN BE WITHDRAWN
SAMPLES ARE CODED AND FINNGEN CAN NOT
IDENTIFY PARTICIPANTS
01
02
03
GENOME DATA, ANALYZED AND
PRODUCED FROM BIOBANK SAMPLES, IS
OWNED BY FINNISH BIOBANKS

27. 27

28. 28
Success with from analyzing first 146,000 participants

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Examples:
New loci discovered based on
the Finnish population structure

30. 30

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Variant enriched in Finland, has a strong effect on disease
Also enriched to anchylosing spondylitis and iritis

32. 32

33. 33
Type 2 diabetes
TCFL2
CCND2
CDKAL1 FTO
17512 cases, 114083 controls - >30 independent hits
= Finnish-enriched low-frequency hits, not in Mahajan 201
IGF2BP2
IRS2
MTNR1BWFS1

34. 34
Finnish-enriched
T2D GWAS hit
Missense AKT2:p.Pro50Thr
p = 2.4e-8
Published by Manning et al last year
From METSIM & T2D Genes Finnish studies

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Longitudinal analyses

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E4_DM2_STRICT (T2D) -> DM_NEPHROPATHY

37. 37
DM2_STRICT -> DM_NEPHROPATHY
chr3_127730888_G_A (rs187268162)
Intronic in gene MGLL
• AF: 0.093%
• In survival analysis
Beta: 10.8(1.95), P-Survival= 3.3 x10-8
• In logistic mixed model for case-control
Beta: 7.73(1.48), P-Logistic= 1.72x10-7
Monoacylglycerol lipase (MGLL or MGAL) has
been reported as a potential pharmaceutical
target for reducing neuropathic pain (Crowe MS,
et al. 2015)

38. 38
Partnership with Estonia

39. TNRC18, novel
RNF186
IL23R
FCGR2A
C1orf106
IL10
MST1
MHC
NKX2-3
EMSY
UBAC2

40. 40
Sini Kerminen, Matti Pirinen Georgi Hudjashov, Mait Metspalu

41. 6 ESTONIAN GENOME CENTER
COMPETENCIES
Recruitment – Estonian Biobank Phase 2
16
10638
6098
5611
5729
6089
12596
17675
21086
19740
6146
6183
7314
4758
4264
5233
2829
4069
4893
4311
0
5000
10000
15000
20000
25000
M
ar-19
Apr-19
M
ay-19
Jun-19
Jul-19
Aug-19
Sep-19
Oct-19
Nov-19
Dec-19
Jan-20
Feb-20
M
ar-20
Apr-20
M
ay-20
Jun-20
Jul-20
Aug-20
Sep-20
Oct-20
Samples per month52016
62654
68752
74363
80092
86181
98777
116452
137538
157278
163424
169607
176921
181679
185943
191176
194005
198074
202967
207278
0
50000
100000
150000
200000
250000
M
ar-19
Apr-19
M
ay-19
Jun-19
Jul-19
Aug-19
Sep-19
Oct-19
Nov-19
Dec-19
Jan-20
Feb-20
M
ar-20
Apr-20
M
ay-20
Jun-20
Jul-20
Aug-20
Sep-20
Oct-20
Total samples
Genotyping now completed on
150,000 on Estonia customized
Illumina GSA array
Tonu Esko

42. 42
Global Biobank Network

43. 43
Towards Global
Partnership
Meta-analysis

44. 44
China Kadoorie
Biobank
100k
UK Biobank
500k
FinnGen
180k
Biobank Japan
200k
HUNT Study
70k
Biobank Meta-analysis Initiative
> 2 million genotyped samples
BioVu
120k
BioME
32k
UCLA Precision Health Biobank
14k
Michigan Genome Initiative
47k
Partners
Biobank
25k
Colorado Biobank
30k
Estonian Biobank
150k
Generation
Scotland
24k
Million Veteran Program
500k
deCODE Genetics
250k
East London Genes & Health
36k
LifeLines NL
52K
Mexico City
*genotyped sample sizes

45. 45
Locus Discovery

46. 46
Asthma
Biobank Japan
8,204 cases, 10 loci
UK Biobank
26,332 cases, 31 loci Combined
52,194 cases, 52 loci
Finngen
12,071 cases, 8 loci
HUNT
5,587 cases, 3 loci
Wei Zhou, Masa Kanai, Juha Karjalainen

47. 47
Fine-Mapping

48. 48
Example: MYOC region
FinnGen
Missense variants in MYOC
previously associated to
Juvenile Open Angle
Galucoma

49. 49
Example: MYOC region
UKBB

50. 50
Example: MYOC region
MYOC:Q368X
FinnGen + UKBB
Trans-ethnic fine-mapping pinpoints the

51. 51
rs74315329 in MYOC
H7_GLAUCOMA
Beta=1.72(0.21)
P=2.86x10-16
H7_GLAUCOMA -> H7_GLAUCOMA_OPER
Beta=1.13(0.45),
P-Survival=0.012
Population: ’Survival’ from Glaucoma
Glaucoma Patients: ’Survival’ from Surgery

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● The power of large genetic isolate
● The power of National Health Records
● The power of global collaborations

53. AcknowledgementsAcknowledgements